WO2019019596A1

WO2019019596A1 - Breakpoint list processing method, device, server and medium

Info

Publication number: WO2019019596A1
Application number: PCT/CN2018/074883
Authority: WO
Inventors: 徐光飞
Original assignee: 平安科技（深圳）有限公司
Priority date: 2017-07-24
Filing date: 2018-01-31
Publication date: 2019-01-31
Also published as: CN107688959A; CN107688959B

Abstract

Provided in the present scheme are a method and device for processing a breakpoint list, a server and a medium, applicable to the technical field of auto insurance sales. The method comprises: obtaining target breakpoint lists to be assigned to sales agents, each target breakpoint list comprising more than one list attribute; calculating an attribute score corresponding to each list attribute of each target breakpoint list, wherein the attribute score of the list attribute is positively correlated with the proportion of the list attribute in a historical breakpoint list of successful sales; and performing the following steps for each of the target breakpoint lists: determining, according to each attribute score calculated under one target breakpoint list, a list score of the one target breakpoint list; sequentially assigning each of the target breakpoint lists to a sales agent according to the respective list score corresponding to each target breakpoint lists from high to low. The present technical solution is used to resolve the difficulty for sales agents in distinguishing favorable from unfavorable breakpoint lists, which leads to low turnover rates for a sales agent.

Description

Method, device, server and medium for processing breakpoint list

This application claims the priority of the Chinese Patent Application filed on July 24, 2017, the Chinese Patent Office, the application number is 201710605626.9, and the invention is entitled "Processing method of the breakpoint list, storage medium and server", the entire contents of which are incorporated by reference. In this application.

Technical field

The present application belongs to the technical field of automobile insurance sales, and in particular, to a method, a device, a server and a medium for processing a breakpoint list.

Background technique

At present, the auto insurance sales website generally collects a list of users' breakpoints in order to dig out potential sales customers. The breakpoint list refers to the data that the user performs browsing and other related operations on the auto insurance sales website, and the transaction is not completed. For example, the owner wants to know the auto insurance quotation, enters the name, license plate, mobile phone and other information on the auto insurance sales website for quotation, but does not carry out subsequent insurance operations. The back-end system collects similar data, which is called a breakpoint list. The subsequent list of breakpoints is provided to the sales agent for follow-up, so that the users in the breakpoint list can be insured for auto insurance.

However, the collected breakpoint list has a large amount of data, a large number of attributes and high quality. In the process of sales agent follow-up, it is difficult to distinguish the advantages and disadvantages of these breakpoint lists, resulting in a low turnover rate of sales agents.

technical problem

In view of this, the embodiment of the present application provides a method, a device, a server, and a medium for processing a breakpoint list, so as to solve the problem that a business conversion rate of a sales agent is low.

Technical solution

A first aspect of the embodiment of the present application provides a method for processing a breakpoint list, including:

Obtain a list of each target breakpoint to be assigned to the sales agent, and each target breakpoint list includes more than one list attribute;

Calculating an attribute score corresponding to each list attribute of each target breakpoint list, where the attribute score of the list attribute is positively correlated with a proportion of the list attribute in a historical breakpoint list of successful sales;

Performing each of the target breakpoint lists separately: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list;

Each of the target breakpoint lists is sequentially assigned to the sales agent according to the respective list scores of the respective target breakpoint lists from high to low.

A second aspect of the embodiments of the present application provides a processing device for a breakpoint list, including:

a target list obtaining module, configured to obtain each target breakpoint list to be allocated to a sales agent, and each target breakpoint list includes one or more list attributes;

An attribute score calculation module, configured to calculate an attribute score corresponding to each list attribute of each of the target breakpoint lists, where the attribute score of the list attribute is occupied by the list attribute in a historical breakpoint list of successful sales The size of the scale is positively correlated;

a list score calculation module, configured to separately perform each of the target breakpoint lists: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list;

The breakpoint list allocation module is configured to sequentially allocate each of the target breakpoint lists to the sales agent according to the respective list scores of the respective target breakpoint lists.

A third aspect of an embodiment of the present application provides a server including a memory and a processor, the memory storing computer readable instructions executable on the processor, the processor executing the computer readable The steps of the method for processing the breakpoint list as described in the first aspect.

A fourth aspect of the embodiments of the present application provides a computer readable storage medium storing computer readable instructions, the computer readable instructions being executed by a processor to implement the first aspect as described in the first aspect The steps of the processing method of the breakpoint list.

Beneficial effect

In the embodiment of the present application, first, each target breakpoint list to be allocated to a sales agent is obtained, and each target breakpoint list includes one or more list attributes; and then, each list attribute of each target breakpoint list is calculated. Attribute score, the attribute score of the list attribute is positively correlated with the proportion of the list attribute in the historical breakpoint list of the sales success; and then, each of the target breakpoint lists is respectively executed: according to one Each attribute score calculated under the target breakpoint list determines a list score of the one target breakpoint list; and finally, each of the target breakpoint lists is ranked according to each of the target breakpoint lists corresponding to the list score from high to low. Assigned to sales agents in turn. In this way, the list attributes of the list of breakpoints can be scored separately, and the scores of the list of each breakpoint list are determined according to the scores of each list attribute after the score, so that the scores of the list of breakpoints are distinguished according to the scores of the lists, and the list is scored. The higher the value, the better the list of breakpoints. When assigning to a sales agent, the scores are assigned from high to low according to the list, that is, the quality breakpoint list is preferentially assigned. In this way, the salesperson's current breakpoint list is the highest quality breakpoint list in the same batch, which can improve the business conversion rate of the sales agent.

DRAWINGS

FIG. 1 is a flowchart of an embodiment of a method for processing a breakpoint list according to an embodiment of the present application;

2 is a schematic flowchart of step 102 of a method for processing a breakpoint list in an application scenario according to an embodiment of the present application;

FIG. 3 is a schematic flowchart of step 102 of a method for processing a breakpoint list in another application scenario according to an embodiment of the present disclosure;

FIG. 4 is a schematic flowchart of a method for processing a breakpoint list in step 102 of a method for presetting a preset attribute score in another application scenario;

FIG. 5 is a structural diagram of an embodiment of a processing device for a breakpoint list according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a server according to an embodiment of the present application.

Embodiments of the invention

In the following description, for purposes of illustration and description However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the application.

In order to explain the technical solutions described in the present application, the following description will be made by way of specific embodiments.

Referring to FIG. 1 , an embodiment of a method for processing a breakpoint list in the embodiment of the present application includes:

101. Obtain a list of target breakpoints to be allocated to the sales agent, and each target breakpoint list includes more than one list attribute;

In this embodiment, after the user performs related operations on the auto insurance sales website and finally fails to complete the insurance, the system collects the operation information of the users and generates a list of each breakpoint. Before assigning these breakpoint lists to sales agents, the quality of these breakpoint lists needs to be evaluated, so that the more quality breakpoint lists are assigned to the sales agents as soon as possible. This is because when the number of visitors to the auto insurance sales website is huge, the data of the breakpoint list collected by the system in real time is very large, and the processing capacity or task capacity of the sales agent is limited. Therefore, providing high-quality breakpoint lists to sales agents for processing can effectively increase the business conversion rate of sales agents to these breakpoint lists and improve the performance of auto insurance sales.

Understandably, in general, a good list of breakpoints usually has the characteristics of complete attributes, such as the user name of the user recorded on the first breakpoint list, and the user name and phone number of the second breakpoint list. number. Obviously, the list attribute of the second breakpoint list can help the sales agent to sell more smoothly and complete the business conversion, so the second breakpoint list is better than the first breakpoint list.

Specifically, the target breakpoint list may include one, two or more of the list attributes listed below; for example, the list attribute is a phone number, a license plate number, a frame number, an engine number, a quoted price, and a Insured, renewed or new car insurance.

The above telephone number, license plate number, frame number, and engine number are the contact information and vehicle related information entered by the user on the auto insurance sales website. The above-mentioned "quoted" attribute means that when the user operates on the vehicle sales website, the vehicle sales website has provided the quotation information of a certain automobile insurance according to the operation of the user, for example, the quotation page of the automobile insurance A is displayed. The above-mentioned "insured" list attribute means that the user has completed at least one insurance on the vehicle sales website. Since such users are regarded as "old customers", the list of "insured" is viewed. Do the key attribute information. The above-mentioned "renewal" list attribute refers to the user's renewed related operation on the vehicle sales website or browsed the related page of renewal. The above-mentioned "new car insurance type" list attribute refers to the user browsing the new auto insurance type on the auto insurance sales website. For example, the user has already insured or has visited the auto insurance B. When the user subsequently browses the auto insurance C on the auto insurance sales website, , the list of breakpoints generated this time has the list attribute of “new car insurance”.

102. Calculate an attribute score corresponding to each list attribute of each target breakpoint list, where the attribute score of the list attribute is positively correlated with a proportion of the list attribute in a historical breakpoint list of successful sales. ;

After determining the target breakpoint list, it is necessary to calculate the attribute scores for each of the target list attributes in each target breakpoint list in each target breakpoint list. For example, there are two target breakpoint lists. The target breakpoint list a has three list attributes, namely a1, a2, and a3; the target breakpoint list b has three list attributes, namely b1, b2, and b3; Therefore, it is necessary to separately calculate the attribute scores corresponding to each of a1, a2, a3, b1, b2, and b3. The calculated attribute scores corresponding to a1, a2, and a3 belong to the target breakpoint list a, and the calculated attribute scores corresponding to b1, b2, and b3 belong to the target breakpoint list b.

In this embodiment, the attribute score corresponding to the calculated list attribute is used for subsequent calculation of the list score of each target breakpoint list, and the list score determines the pros and cons of the target break list, and the list score is higher. The higher the target breakpoint list is. For this reason, for the attribute score corresponding to each list attribute, the more useful the list attribute is required, the corresponding calculated attribute score should be higher.

Therefore, in this embodiment, the level of the attribute score of the calculated list attribute is required to be positively correlated with the proportion of the list attribute in the historical breakpoint list of the successful sales, that is, the list attribute is successfully sold. The larger the proportion of the historical breakpoint list, the higher the corresponding attribute score; conversely, the smaller the proportion of the list attribute in the historical breakpoint list of sales success, the lower the corresponding attribute score. It can be understood that if there are 10 historical breakpoint lists for successful sales, 9 of the breakpoint lists have the list attribute d, that is, the historical breakpoint list with 90% of sales success has the list attribute d, which can be considered as the list. Attribute d is of great help to the sales success of the historical breakpoint list; if there are 10 historical breakpoint lists for successful sales, only one breakpoint list has the list attribute e, that is, the historical breakpoint list with 10% sales success has The list attribute e, at this time, can be considered that the list attribute e is less helpful for the sales success of the historical breakpoint list. Undoubtedly, the list attribute d has a larger proportion in the historical breakpoint list of the sales success than the list attribute e. Accordingly, the attribute attribute corresponding to the list attribute d should be higher than the list attribute e, for example, For example, the attribute attribute corresponding to the list attribute d is 0.9, and the attribute attribute corresponding to the list attribute e is 0.1.

Specifically, in this embodiment, the following two methods may be used to calculate the attribute score corresponding to the list attribute. As shown in FIG. 2 and FIG. 3, the two methods have advantages and disadvantages, and may be selected and used according to actual conditions.

The first method: as shown in FIG. 2, the foregoing step 102 may include:

201. Determine a target list attribute that needs to calculate an attribute score currently;

202. Count the first number of the breakpoint list having the target list attribute in the historical breakpoint list of the sales success;

203. Calculate a first proportion of the first number of breakpoint lists in the historical breakpoint list;

204. Determine, according to the first ratio, an attribute score corresponding to the target list attribute. The larger the first ratio is, the higher the determined attribute score is.

For step 201, since each attribute attribute under each target breakpoint list needs to separately calculate the corresponding attribute score, in the calculation, multiple threads may be used, and each thread processes a list attribute calculation. In a thread, the list attribute currently calculating the attribute score is determined as the target list attribute.

For step 202, it can be understood that, for the collected breakpoint list, after the breakpoint list is assigned to the sales agent, the sales agent will feed back the results of the breakpoint list processing to the system. Therefore, the system can know which breakpoint list in the historical breakpoint list is successfully sold, and which breakpoint list sales fail. In this embodiment, assuming that there are a total of 100 historical breakpoint lists for successful sales on the system, step 202 is to count how many breakpoint lists in the 100 historical breakpoint lists have the target list attribute. It can be seen from the above that the first quantity can reflect how much the target list attribute helps the sales success of the breakpoint list. The larger the first quantity, the more helpful the target list attribute is to the successful sale of the break list. Big.

For step 203, assuming a total of 100 successful historical breakpoint lists on the system, the first number is 40, and the first ratio is 40%.

For step 204, a conversion relationship between the first ratio and the attribute score may be preset on the system. In particular, the value of the first ratio may be a 1:1 relationship with the value of the attribute score. That is, when the first ratio is 40%, the attribute score may be 0.4. In this embodiment, the conversion relationship between the first ratio and the attribute score is not specifically limited, but the first ratio is required to be positively correlated with the attribute score, that is, the larger the first ratio is, the higher the attribute score is determined; The smaller the first ratio, the lower the determined attribute score.

The second method: as shown in FIG. 3, the foregoing step 102 may include:

301. Determine a target list attribute that needs to calculate an attribute score currently;

302. Query a preset attribute score corresponding to the target list attribute.

303. Determine the preset attribute score as an attribute score corresponding to the target list attribute.

The foregoing step 301 is similar to the foregoing step 201, and details are not described herein again.

For the step 302, the preset attribute score corresponding to the target list attribute may be pre-stored on the system, and the preset attribute score corresponding to the target list attribute may be directly queried on the system when needed.

As shown in FIG. 4, the preset attribute score corresponding to the target list attribute may be preset by the following steps:

401. Periodically count the second number of the breakpoint list having the target list attribute in the historical breakpoint list of the sales success;

402. Calculate a second proportion of the second number of breakpoint lists in the historical breakpoint list;

403. Determine, according to the second ratio, a preset attribute score corresponding to the target list attribute. The larger the second ratio is, the higher the determined preset attribute score is.

For steps 401~403, the system can periodically perform a second number of statistics, such as monthly, weekly, or daily statistics. The process of counting the second quantity is similar to the process of counting the first quantity in the above step 202, and details are not described herein again. After calculating the second quantity of the target list attribute, calculating a second proportion of the second number of breakpoint lists in the historical breakpoint list, and then determining, according to the second ratio, the target list attribute Corresponding preset attribute score. In this embodiment, the conversion relationship between the second ratio and the preset attribute score is not specifically limited, but the second ratio is required to be positively correlated with the preset attribute score, that is, the larger the second ratio is determined. The higher the preset attribute score is; on the contrary, the smaller the second ratio is, the lower the determined preset attribute score is. It can be seen that the system can calculate and store the corresponding preset attribute scores for different target list attributes periodically, and when needed, the query system can obtain the preset attribute score corresponding to the target list attribute.

For step 303, the queried preset attribute score is determined as an attribute score corresponding to the target list attribute.

It can be seen from the above that the comparison between the first method and the second method has its advantages and disadvantages. The advantage of the first method is that the real-time performance is strong. Since the attribute scores corresponding to each target list attribute are calculated in real time according to the historical breakpoint list data of the sales success on the system, the calculated attribute score corresponding to the target list attribute is calculated. More accurate and more real-time, but the disadvantage is that the consumption of system computing resources is large; the advantage of the second method is that the consumption of system computing resources is small, and the system only needs to periodically pre-review the data according to the historical list of successful sales. The preset attribute scores corresponding to the respective list attributes are calculated and stored. When it is necessary to obtain the preset attribute score corresponding to a target list attribute, the query can be performed on the system, and no real-time calculation is needed, so the consumption of the computing resource is small, but the disadvantage is that the attribute score corresponding to the determined target list attribute is real-time. Poor sex, there may be problems with low accuracy.

Therefore, when step 102 is executed, the first method or the second method may be selected according to actual conditions.

For ease of understanding, when the target breakpoint list contains list attributes such as phone number, license plate number, frame number, engine number, quoted price, insured, renewed insurance, or new auto insurance type, in an application scenario, specific list The attribute score corresponding to the attribute can be determined accordingly as follows:

1) If it is known that all the successful breakpoint lists have complete phone numbers, the attribute value corresponding to the "phone number" list attribute may be 1;

2) If it is known that the breakpoint list of 80% of sales success has a complete license plate number, the attribute score corresponding to the list attribute of "the license plate number" may be 0.8;

3) If the statistics show that 40% of the successful breakpoint list has complete three items (license plate number, frame number, engine number), the attribute attribute corresponding to the list attribute of “car three items” may be 0.4. ;

4) If it is known that the breakpoint list of 70% of sales successes is quoted, the attribute score corresponding to the list attribute of “quoted” may be 0.7;

5) If it is known that the breakpoint list of 80% of sales successes is insured, the attribute score corresponding to the list attribute of “insured” may be 0.8;

6) If it is known that the 60% of the successful breakpoint list is renewed, the attribute attribute corresponding to the list attribute of “Renewal” may be 0.6;

7) If it is known that the list of 40% successful sales breakpoints is a new type of auto insurance, the attribute score corresponding to the list attribute of the “new auto insurance type” may be 0.4.

103. Perform, respectively, performing each of the target breakpoint lists: determining, according to each attribute score calculated under a target breakpoint list, a list score of the one target breakpoint list;

After calculating the attribute scores corresponding to each list attribute in each target breakpoint list in each target breakpoint list, it is necessary to separately calculate the list score of each target breakpoint list. The list score of a target breakpoint list is determined by the attribute score corresponding to each list attribute under the target breakpoint list. Therefore, the step of determining the list score is performed separately for each of the target breakpoint lists: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list.

Specifically, the manner of determining the list score in the foregoing step 103 includes at least the following four types, and any one of the list scores may be selected according to actual conditions.

Method 1: Calculate the sum of the scores of the various attributes calculated under a target breakpoint list as the list score of the one target breakpoint list. For example, at a certain breakpoint target scores were each attribute lists S1, S2, S3, ......, Sn, then the list of the target breakpoint list _total score S = S1 + S2 + S3 + ...... + Sn.

Manner 2: linearly accumulating each attribute score calculated under a target breakpoint list to obtain a first accumulated value, and then calculating an average value of the first accumulated value for each list attribute of the one target breakpoint list as The list of the target breakpoint list is scored. For example, if the scores of each attribute under a target breakpoint list are S1, S2, S3, ..., Sn, respectively, the first accumulated value of the target breakpoint list is S _plus = S1 + S2 + S3 + ... + Sn. A list of the target breakpoint list score S = S _are _added / n = (S1 + S2 + S3 + ...... + Sn) / n.

Manner 3: Calculate the variance of the one target breakpoint list according to each attribute score calculated under a target breakpoint list, as the list score of the one target breakpoint list. For example, if the scores of each attribute under a target breakpoint list are S1, S2, S3, ..., Sn, then the list of the target breakpoint list scores S _variance ² = ((S1-S _average ) ² + (S2- _each ^{S) 2 + ... + (Sn-} S _-average) ²⁾ / n, where _both S = (S1 + S2 + S3 + ...... + Sn) / n.

Method 4: Calculate the standard deviation of the one target breakpoint list according to each attribute score calculated under a target breakpoint list, as the list score of the one target breakpoint list. For example, if each attribute score under a target breakpoint list is S1, S2, S3, ..., Sn, then the list score of the target breakpoint list S _{standard deviation} = the square root of the above S _variance ² .

104. All the target breakpoint lists are sequentially allocated to the sales agents according to the respective list scores of the respective target breakpoint lists from high to low.

It can be understood that after calculating the list score corresponding to each target breakpoint list, it can be known that the higher the list break score, the better the target breakpoint list, and the lower the list score, the worse the target breakpoint list is. Therefore, in order to improve sales The overall business conversion rate of the agent should be assigned to the sales agent in turn according to the list score from high to low, so that the list of breakpoints currently received by the sales agent is the highest quality in the same batch. The list of breakpoints, which in turn can effectively increase the business conversion rate of sales agents.

In this embodiment, first, each target breakpoint list to be allocated to a sales agent is obtained, and each target breakpoint list includes one or more list attributes; and then, each list attribute of each target breakpoint list is calculated. An attribute score, the level of the attribute score of the list attribute is positively correlated with the proportion of the list attribute in the historical breakpoint list of the sales success; and then, each of the target breakpoint lists is respectively executed: according to a target Each attribute score calculated under the breakpoint list determines a list score of the one target breakpoint list; finally, each of the target breakpoint lists is sequentially ranked according to each of the target breakpoint lists Assigned to sales agents. In this way, the list attributes of the list of breakpoints can be scored separately, and the scores of the list of each breakpoint list are determined according to the scores of each list attribute after the score, so that the scores of the list of breakpoints are distinguished according to the scores of the lists, and the list is scored. The higher the value, the better the list of breakpoints. When assigning to a sales agent, the scores are assigned from high to low according to the list, that is, the quality breakpoint list is preferentially assigned. In this way, the salesperson's current breakpoint list is the highest quality breakpoint list in the same batch, which can improve the business conversion rate of the sales agent.

It should be understood that the size of the sequence of the steps in the above embodiments does not mean that the order of execution is performed. The order of execution of each process should be determined by its function and internal logic, and should not be construed as limiting the implementation process of the embodiments of the present application.

The above mainly describes a method for processing a breakpoint list, and a processing device for a breakpoint list will be described in detail below.

FIG. 5 is a structural diagram showing an embodiment of a processing device for a breakpoint list in the embodiment of the present application.

In this embodiment, a processing device for a breakpoint list includes:

The target list obtaining module 501 is configured to obtain each target breakpoint list to be allocated to the sales agent, and each target breakpoint list includes one or more list attributes;

The attribute score calculation module 502 is configured to calculate an attribute score corresponding to each list attribute of each of the target breakpoint lists, where the attribute score of the list attribute is in a historical breakpoint list of the list of successful sales The proportion of the proportion is positively correlated;

The list score calculation module 503 is configured to separately perform each of the target breakpoint lists: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list;

The breakpoint list allocation module 504 is configured to sequentially allocate each of the target breakpoint lists to the sales agent according to the list score corresponding to each of the target breakpoint lists.

Further, the attribute score calculation module may include:

a first attribute determining unit, configured to determine a target list attribute that currently needs to calculate an attribute score;

a first quantity statistics unit, configured to count a first number of breakpoint lists having the target list attribute in the historical breakpoint list of the sales success;

a first ratio calculation unit, configured to calculate a first proportion of the first number of breakpoint lists in the historical breakpoint list;

The first score determining unit is configured to determine an attribute score corresponding to the target list attribute according to the first ratio, and the larger the first ratio, the higher the determined attribute score.

Further, the attribute score calculation module may include:

a second attribute determining unit, configured to determine a target list attribute that currently needs to calculate an attribute score;

a score query unit, configured to query a preset attribute score corresponding to the target list attribute;

a second score determining unit, configured to determine the preset attribute score as an attribute score corresponding to the target list attribute;

The preset attribute score corresponding to the target list attribute may be preset by the following module:

a second quantity statistic module, configured to periodically count the second number of the breakpoint list having the target list attribute in the historical breakpoint list of the sales success;

a second ratio calculation module, configured to calculate a second proportion of the second number of breakpoint lists in the historical breakpoint list;

The preset score determining module is configured to determine a preset attribute score corresponding to the target list attribute according to the second ratio, and the second ratio is larger, the determined preset attribute score is higher.

Further, the list score calculation module may include:

a first list score calculation unit, configured to calculate a sum of respective attribute scores calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

The accumulating unit is configured to linearly accumulate each attribute score calculated under a target breakpoint list to obtain a first accumulated value;

a second list score calculation unit, configured to calculate a mean value of each of the list attributes of the first target breakpoint list as the list score of the one target breakpoint list;

or

a third list score calculation unit, configured to calculate a variance of the one target breakpoint list according to each attribute score calculated under a target breakpoint list, as a list score of the one target breakpoint list;

or

And a fourth list score calculation unit, configured to calculate a standard deviation of the one target breakpoint list according to each attribute score calculated under a target breakpoint list, as a list score of the one target breakpoint list.

Further, the target breakpoint list may include one, two or more of the list attributes listed below;

The list attributes are phone number, license plate number, frame number, engine number, quoted price, insured, renewed insurance or new auto insurance.

FIG. 6 is a schematic diagram of a server according to an embodiment of the present application. As shown in FIG. 6, the server 6 of this embodiment includes a processor 60 and a memory 61 in which computer readable instructions 62 executable on the processor 60, such as a breakpoint list, are stored. The procedure for processing methods. The processor 60 executes the computer readable instructions 62 to implement the steps in the method for processing the various breakpoint lists described above, such as steps 101 through 104 shown in FIG. Alternatively, the processor 60, when executing the computer readable instructions 62, implements the functions of the various modules/units in the various apparatus embodiments described above, such as the functions of the modules 501 through 504 shown in FIG.

Illustratively, the computer readable instructions 62 may be partitioned into one or more modules/units that are stored in the memory 61 and executed by the processor 60, To complete this application. The one or more modules/units may be a series of computer readable instruction segments capable of performing a particular function, the instruction segments being used to describe the execution of the computer readable instructions 62 in the server 6.

The server 6 can be a computing device such as a local server or a cloud server. The server may include, but is not limited to, a processor 60, a memory 61. It will be understood by those skilled in the art that FIG. 6 is merely an example of the server 6, and does not constitute a limitation to the server 6, and may include more or less components than those illustrated, or some components may be combined, or different components, such as The server may also include an input and output device, a network access device, a bus, and the like.

The processor 60 can be a central processing unit (Central Processing Unit, CPU), can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor or any conventional processor or the like.

The memory 61 may be an internal storage unit of the server 6, such as a hard disk or a memory of the server 6. The memory 61 may also be an external storage device of the server 6, such as a plug-in hard disk equipped on the server 6, a smart memory card (SMC), and a Secure Digital (SD) card. Flash card, etc. Further, the memory 61 may also include both an internal storage unit of the server 6 and an external storage device. The memory 61 is for storing the computer readable instructions and other programs and data required by the server. The memory 61 can also be used to temporarily store data that has been output or is about to be output.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application, in essence or the contribution to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .

The above embodiments are only used to explain the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still The technical solutions described in the embodiments are modified, or the equivalents of the technical features are replaced by the equivalents. The modifications and substitutions of the embodiments do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

A method for processing a breakpoint list, comprising:

Obtain a list of each target breakpoint to be assigned to the sales agent, and each target breakpoint list includes more than one list attribute;

Calculating an attribute score corresponding to each list attribute of each target breakpoint list, where the attribute score of the list attribute is positively correlated with a proportion of the list attribute in a historical breakpoint list of successful sales;

Performing each of the target breakpoint lists separately: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list;

Each of the target breakpoint lists is sequentially assigned to the sales agent according to the respective list scores of the respective target breakpoint lists from high to low.
The method for processing a breakpoint list according to claim 1, wherein the calculating an attribute score corresponding to each list attribute of each of the target breakpoint lists comprises:

Determining the target list attribute of the current attribute score to be calculated;

Counting the first number of breakpoint lists with the target list attribute in the historical breakpoint list of sales success;

Calculating a first proportion of the first number of breakpoint lists in the historical breakpoint list;

Determining an attribute score corresponding to the target list attribute according to the first ratio. The larger the first ratio is, the higher the determined attribute score is.
The method for processing a breakpoint list according to claim 1, wherein the calculating an attribute score corresponding to each list attribute of each of the target breakpoint lists comprises:

Determining the target list attribute of the current attribute score to be calculated;

Querying a preset attribute score corresponding to the target list attribute;

Determining the preset attribute score as an attribute score corresponding to the target list attribute;

The preset attribute score corresponding to the target list attribute is preset by the following steps:

Regularly counting the second number of breakpoint lists having the target list attribute in the historical breakpoint list of sales success;

Calculating a second proportion of the second number of breakpoint lists in the historical breakpoint list;

Determining a preset attribute score corresponding to the target list attribute according to the second ratio. The larger the second ratio is, the higher the determined preset attribute score is.
The method for processing a breakpoint list according to claim 1, wherein the determining the list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list comprises:

Calculating a sum of scores of the respective attributes calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

Performing a linear accumulation of each attribute score calculated under a target breakpoint list to obtain a first accumulated value;

Calculating, by the first accumulated value, a mean value of each list attribute under the one target breakpoint list as a list score of the one target breakpoint list;

or

Calculating a variance of the one target breakpoint list according to each attribute score calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

Calculating a standard deviation of the one target breakpoint list according to each attribute score calculated under a target breakpoint list as a list score of the one target breakpoint list.
The method for processing a breakpoint list according to any one of claims 1 to 4, wherein the target breakpoint list includes one, two or more of the list attributes listed below;

The list attributes are phone number, license plate number, frame number, engine number, quoted price, insured, renewed insurance or new auto insurance.
A processing device for a breakpoint list, comprising:

a target list obtaining module, configured to obtain each target breakpoint list to be allocated to a sales agent, and each target breakpoint list includes one or more list attributes;

An attribute score calculation module, configured to calculate an attribute score corresponding to each list attribute of each of the target breakpoint lists, where the attribute score of the list attribute is occupied by the list attribute in a historical breakpoint list of successful sales The size of the scale is positively correlated;

a list score calculation module, configured to separately perform each of the target breakpoint lists: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list;

The breakpoint list allocation module is configured to sequentially allocate each of the target breakpoint lists to the sales agent according to the respective list scores of the respective target breakpoint lists.
The apparatus for processing a breakpoint list according to claim 6, wherein the attribute score calculation module comprises:

a first attribute determining unit, configured to determine a target list attribute that currently needs to calculate an attribute score;

a first quantity statistics unit, configured to count a first number of breakpoint lists having the target list attribute in the historical breakpoint list of the sales success;

a first ratio calculation unit, configured to calculate a first proportion of the first number of breakpoint lists in the historical breakpoint list;

The first score determining unit is configured to determine an attribute score corresponding to the target list attribute according to the first ratio, and the larger the first ratio, the higher the determined attribute score.
The apparatus for processing a breakpoint list according to claim 6, wherein the attribute score calculation module comprises:

a second attribute determining unit, configured to determine a target list attribute that currently needs to calculate an attribute score;

a score query unit, configured to query a preset attribute score corresponding to the target list attribute;

a second score determining unit, configured to determine the preset attribute score as an attribute score corresponding to the target list attribute;

The preset attribute score corresponding to the target list attribute may be preset by the following module:

a second quantity statistic module, configured to periodically count the second number of the breakpoint list having the target list attribute in the historical breakpoint list of the sales success;

a second ratio calculation module, configured to calculate a second proportion of the second number of breakpoint lists in the historical breakpoint list;

The preset score determining module is configured to determine a preset attribute score corresponding to the target list attribute according to the second ratio, and the second ratio is larger, the determined preset attribute score is higher.
The apparatus for processing a breakpoint list according to claim 6, wherein the list score calculation module comprises:

a first list score calculation unit, configured to calculate a sum of respective attribute scores calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

The accumulating unit is configured to linearly accumulate each attribute score calculated under a target breakpoint list to obtain a first accumulated value;

a second list score calculation unit, configured to calculate a mean value of each of the list attributes of the first target breakpoint list as the list score of the one target breakpoint list;

or

a third list score calculation unit, configured to calculate a variance of the one target breakpoint list according to each attribute score calculated under a target breakpoint list, as a list score of the one target breakpoint list;

or

And a fourth list score calculation unit, configured to calculate a standard deviation of the one target breakpoint list according to each attribute score calculated under a target breakpoint list, as a list score of the one target breakpoint list.
The apparatus for processing a breakpoint list according to any one of claims 6 to 9, wherein the target breakpoint list includes one, two or more of the list attributes listed below;

The list attributes are phone number, license plate number, frame number, engine number, quoted price, insured, renewed insurance or new auto insurance.
A server, comprising: a memory and a processor, wherein the memory stores computer readable instructions executable on the processor, the processor executing the computer readable instructions to:

Obtain a list of each target breakpoint to be assigned to the sales agent, and each target breakpoint list includes more than one list attribute;

Calculating an attribute score corresponding to each list attribute of each target breakpoint list, where the attribute score of the list attribute is positively correlated with a proportion of the list attribute in a historical breakpoint list of successful sales;

Performing each of the target breakpoint lists separately: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list;

Each of the target breakpoint lists is sequentially assigned to the sales agent according to the respective list scores of the respective target breakpoint lists from high to low.
The server according to claim 11, wherein the calculating an attribute score corresponding to each list attribute of each of the target breakpoint lists comprises:

Determining the target list attribute of the current attribute score to be calculated;

Counting the first number of breakpoint lists with the target list attribute in the historical breakpoint list of sales success;

Calculating a first proportion of the first number of breakpoint lists in the historical breakpoint list;

Determining an attribute score corresponding to the target list attribute according to the first ratio. The larger the first ratio is, the higher the determined attribute score is.
The server according to claim 11, wherein the calculating an attribute score corresponding to each list attribute of each of the target breakpoint lists comprises:

Determining the target list attribute of the current attribute score to be calculated;

Querying a preset attribute score corresponding to the target list attribute;

Determining the preset attribute score as an attribute score corresponding to the target list attribute;

The preset attribute score corresponding to the target list attribute is preset by the following steps:

Regularly counting the second number of breakpoint lists having the target list attribute in the historical breakpoint list of sales success;

Calculating a second proportion of the second number of breakpoint lists in the historical breakpoint list;

Determining a preset attribute score corresponding to the target list attribute according to the second ratio. The larger the second ratio is, the higher the determined preset attribute score is.
The server according to claim 11, wherein the determining the list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list comprises:

Calculating a sum of scores of the respective attributes calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

Performing a linear accumulation of each attribute score calculated under a target breakpoint list to obtain a first accumulated value;

Calculating, by the first accumulated value, a mean value of each list attribute under the one target breakpoint list as a list score of the one target breakpoint list;

or

Calculating a variance of the one target breakpoint list according to each attribute score calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

Calculating a standard deviation of the one target breakpoint list according to each attribute score calculated under a target breakpoint list as a list score of the one target breakpoint list.
The server according to any one of claims 11 to 14, wherein the target breakpoint list comprises one, two or more of the list attributes listed below;

The list attributes are phone number, license plate number, frame number, engine number, quoted price, insured, renewed insurance or new auto insurance.
A computer readable storage medium storing computer readable instructions, wherein the computer readable instructions, when executed by at least one processor, implement the following steps:

Obtain a list of each target breakpoint to be assigned to the sales agent, and each target breakpoint list includes more than one list attribute;

Calculating an attribute score corresponding to each list attribute of each target breakpoint list, where the attribute score of the list attribute is positively correlated with a proportion of the list attribute in a historical breakpoint list of successful sales;

Performing each of the target breakpoint lists separately: determining a list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list;

Each of the target breakpoint lists is sequentially assigned to the sales agent according to the respective list scores of the respective target breakpoint lists from high to low.
The computer readable storage medium according to claim 16, wherein the calculating an attribute score corresponding to each of the list attributes of each of the target breakpoint lists comprises:

Determining the target list attribute of the current attribute score to be calculated;

Counting the first number of breakpoint lists with the target list attribute in the historical breakpoint list of sales success;

Calculating a first proportion of the first number of breakpoint lists in the historical breakpoint list;

Determining an attribute score corresponding to the target list attribute according to the first ratio. The larger the first ratio is, the higher the determined attribute score is.
The computer readable storage medium according to claim 16, wherein the calculating an attribute score corresponding to each of the list attributes of each of the target breakpoint lists comprises:

Determining the target list attribute of the current attribute score to be calculated;

Querying a preset attribute score corresponding to the target list attribute;

Determining the preset attribute score as an attribute score corresponding to the target list attribute;

The preset attribute score corresponding to the target list attribute is preset by the following steps:

Regularly counting the second number of breakpoint lists having the target list attribute in the historical breakpoint list of sales success;

Calculating a second proportion of the second number of breakpoint lists in the historical breakpoint list;

Determining a preset attribute score corresponding to the target list attribute according to the second ratio. The larger the second ratio is, the higher the determined preset attribute score is.
The computer readable storage medium according to claim 16, wherein the determining the list score of the one target breakpoint list according to each attribute score calculated under a target breakpoint list comprises:

Calculating a sum of scores of the respective attributes calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

Performing a linear accumulation of each attribute score calculated under a target breakpoint list to obtain a first accumulated value;

Calculating, by the first accumulated value, a mean value of each list attribute under the one target breakpoint list as a list score of the one target breakpoint list;

or

Calculating a variance of the one target breakpoint list according to each attribute score calculated under a target breakpoint list as a list score of the one target breakpoint list;

or

Calculating a standard deviation of the one target breakpoint list according to each attribute score calculated under a target breakpoint list as a list score of the one target breakpoint list.
The computer readable storage medium according to any one of claims 16 to 19, wherein the target breakpoint list comprises one, two or more of the list attributes listed below;

The list attributes are phone number, license plate number, frame number, engine number, quoted price, insured, renewed insurance or new auto insurance.